As network traffic increases and/or changes, it is necessary to reevaluate techniques for managing traffic. In one example, as more of the functionality expected by users becomes automated, there has been an increase in background traffic, which can include functions such as repairing, rebalancing, backing-up, and recovering. Many of these tasks or traffic items are non-homogeneous and may have different requirements and schedules. Background traffic is just one kind of traffic which can be managed, and its management must also be combined with management of other communication, e.g., storage traffic.
Existing techniques for managing background traffic were somewhat simple. In some embodiments, first-in-first-out (FIFO) or early-deadline-first (EDF) treatment was given to traffic. In others, linear programming (LP) was used to attempt to determine solutions for completing transmissions or tasks. However, these techniques can mis-prioritize tasks, especially where network topology and requirements are heterogeneous and dynamic. Improper prioritization, scheduling, and/or completion can interfere with performance, cause failure in time-sensitive tasks, increase latency, or otherwise violate quality-of-service (QoS) or Service Level Agreement (SLA) requirements. Some such aspects are described in industry as “noisy neighbor problems.”